In this professional development module, two teaching units focus on the introduction to data science using data exploration and decision trees as an AI method of machine learning. The two teaching units in this module can be used in different ways. They can be taught in sequence or as individual units, depending on the desired focus.

This module uses the free, browser-based software CODAP , with which data exploration and decision trees can be developed interactively without programming.

Lesson 1In the first teaching unit, pupils explore survey data on media use by young people using the web-based data science tool CODAP with a focus on statistical analyses. The application context is an online platform that wants to place targeted advertising for young people for various customers. The pupils examine the multivariate data set under various questions and develop project-based analyses and interpretations, which they present at the end of the lesson. The focus is on the content area of data and information. The unit comprises approx. 8 lessons.
Lesson 2In the second teaching unit, the results from the first unit can be used to create forecasts for various questions using the AI method of decision trees. The focus here is on learning and understanding decision trees as a data-based decision model. The pupils first create decision trees intuitively and manually using the CODAP software based on the data set. The pupils then systematize the creation process step by step in order to understand how an algorithm can automatically create decision trees. Another focus is on the evaluation of finished decision models using test data. The unit comprises approx. 8 lessons.